ArticleFrontiers in immunology2021
Identification of Diagnostic Signatures and Immune Cell Infiltration Characteristics in Rheumatoid Arthritis by Integrating Bioinformatic Analysis and Machine-Learning Strategies.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed, 55 citations in OpenAlex.
- MEOX2: a homeobox transcription factor with multifaceted biological functions and broad disease associations.Frontiers in cell and developmental biology · 2026Review
- Bioinformatics analysis of potential molecular markers and immunological characteristics shared between post-treatment Lyme disease syndrome and rheumatoid arthritis.Frontiers in immunology · 2026Article
- Macrophage-derived exosomes in autoimmune diseases: mechanistic insights and therapeutic implications.Immunologic research · 2025Review
- Weighted Gene Co-expression Network Analysis and Machine Learning Validation for Identifying Major Genes Related to Sjogren's Syndrome.Biochemical genetics · 2025Article
- Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning.Journal of molecular neuroscience : MN · 2025Article
- A Multi-omics approach to identify and validate shared genetic architecture in rheumatoid arthritis, multiple sclerosis, and type 1 diabetes: integrating GWAS, GEO, MSigDB, and scRNA-seq data.Functional & integrative genomics · 2025Article
- Integrative Analyses of Bulk and Single-Cell RNA Seq Identified the Shared Genes in Acute Respiratory Distress Syndrome and Rheumatoid Arthritis.Molecular biotechnology · 2025Article
- Neutrophils: a Central Point of Interaction Between Immune Cells and Nonimmune Cells in Rheumatoid Arthritis.Clinical reviews in allergy & immunology · 2025Review
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- Preliminary evidence of immune infiltration and neutrophil degranulation in peripheral blood of non-obese OSA patients related to cognitive decline.Scientific reports · 2025Article
- Identification of Novel Biomarkers for Ischemic Stroke Through Integrated Bioinformatics Analysis and Machine Learning.Journal of molecular neuroscience : MN · 2025Article
- Individualized diagnosis of rheumatoid arthritis: A rank-based qualitative T cell-related signature.PloS one · 2025Article
- Innovative biomarkers TCN2 and LY6E can significantly inhibit respiratory syncytial virus infection.Journal of translational medicine · 2024Article
- The Effectiveness and Safety of Wu Tou Decoction on Rheumatoid Arthritis-A Systematic Review and Meta-Analysis.Healthcare (Basel, Switzerland) · 2024Review
- Article
- An autoantibody profile identified by human genome-wide protein arrays in rheumatoid arthritis.MedComm · 2024Article
- [Identification of potential biomarkers and immunoregulatory mechanisms of rheumatoid arthritis based on multichip co-analysis of GEO database].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Sinomenine treats rheumatoid arthritis by inhibiting MMP9 and inflammatory cytokines expression: bioinformatics analysis and experimental validation.Scientific reports · 2024Article
- Unveiling the link between lactate metabolism and rheumatoid arthritis through integration of bioinformatics and machine learning.Scientific reports · 2024Article
- The Diagnostic Features of Peripheral Blood Biomarkers in Identifying Osteoarthritis Individuals: Machine Learning Strategies and Clinical Evidence.Current computer-aided drug design · 2024Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Rheumatoid arthritis (RA) refers to an autoimmune rheumatic disease that imposes a huge burden on patients and society. Early RA diagnosis is critical to preventing disease progression and selecting optimal therapeutic strategies more effectively. In the present study, the aim was at examining RA's diagnostic signatures and the effect of immune cell infiltration in this pathology. Methods: Gene Expression Omnibus (GEO) database provided three datasets of gene expressions. Firstly, this study adopted R software for identifying differentially expressed genes (DEGs) and conducting functional correlation analyses. Subsequently, we integrated bioinformatic analysis and machine-learning strategies for screening and determining RA's diagnostic signatures and further verify by qRT-PCR. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. Moreover, this study employed cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) website for assessing the inflammatory state of RA, and an investigation was conducted on the relationship of diagnostic signatures and infiltrating immune cells. Results: On the whole, 54 robust DEGs received the recognition. Lymphocyte-specific protein 1 (LSP1), Granulysin (GNLY), and Mesenchymal homobox 2 (MEOX2) (AUC = 0.955) were regarded as RA's diagnostic markers and showed their statistically significant difference by qRT-PCR. As indicated from the immune cell infiltration analysis, resting NK cells, neutrophils, activated NK cells, T cells CD8, memory B cells, and M0 macrophages may be involved in the development of RA. Additionally, all diagnostic signatures might be different degrees of correlation with immune cells. Conclusions: In conclusion, LSP1, GNLY, and MEOX2 are likely to be available in terms of diagnosing and treating RA, and the infiltration of immune cells mentioned above may critically impact RA development and occurrence.
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